The MuMMI (Multiple Metrics Modeling Infrastructure) project is an infrastructure that facilitates systematic measurement, modeling, and prediction of performance, power consumption and performance-power tradeoffs for parallel systems. In this paper, we present the MuMMI framework, which consists of an Instrumentor, Databases and Analyzer. The MuMMI instrumentor provides for automatic performance and power data collection and storage with low overhead. The MuMMI Databases store performance,

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... r and energy consumption and hardware performance counters' data. The MuMMI Analyzer entails performance and power modeling and performance-power tradeoff and optimizations. As part of the MuMMI project, we mainly focus on discussing the design and development of a MuMMI Instrumentor to provide automatic performance and power data collection and storage with low overhead on multicore systems in detail, then utilize the MuMMI Instrumentor to collect performance and power data for a hybrid MPI/OpenMP earthquake application to discuss application performance-power trade-off and optimizations. Our experimental results show that we reduce up to 8.5% the application execution time and lower up to 18.35% the energy consumption by applying Dynamic Voltage and Frequency Scaling (DVFS), Dynamic Concurrency Throttling (DCT) and loop optimizations.